A new method for augmenting short time series, with application to pain events in sickle cell disease
短时间序列增广新方法及其在镰状细胞病疼痛事件中的应用
Researchers across different fields, including but not limited to ecology, biology, and healthcare, often face the challenge of sparse data. Such sparsity can lead to uncertainties, estimation difficulties, and potential biases in modeling. Here we introduce a novel data augmentation method that combines multiple sparse time series datasets when they share similar statistical properties, thereby improving parameter estimation and model selection reliability. We demonstrate…